In real life scenario, facial expressions and emotions are nothing but responses to the external and internal events of human being. In human computer interaction, recognition of end user's expressions and emotions from the video streaming plays very important role. In such systems it is required to track the dynamic changes in human face movements quickly in order to deliver the required response system. The one real time application is physical fatigue detection based on facial detection and expressions such as driver fatigue detection in order to prevent the accidents on road. Face expression based physical fatigue analysis or detection is out of scope of this paper, but this paper reveal study on different methods those are presented recently for facial expression and/or emotions recognition using video. This paper presenting the methodologies in terms of feature extraction and classification used in facial expression and/or emotion recognition methods with their comparative study. The comparative study is done based on accuracy, implementation tool, advantages and disadvantages. The outcome of this paper is the current research gap and research challenges those are still open to solve for video based facial detection and recognition systems. The survey on recent methods is appropriately presented throughout this paper by considering future research works. © 2017 IEEE.